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most citedTowards End-to-End Deep Learning for Autonomous Racing: On Data Collection and a Unified Architecture for Steering and Throttle Prediction

11 citations · 19 across the 8 of their papers we have counts for

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cs.LG2025

Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data

Abhijit Chunduru, Majid Morafah, Mahdi Morafah +2

The inevitable presence of data heterogeneity has made federated learning very challenging. There are numerous methods to deal with this issue, such as local regularization, better…